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We generate high-quality evidence to advance healthcare policies and practices with the goal of improving the lives of all people affected by serious illness and removing the barriers to health equity that seriously ill patients commonly face.

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PhD

Wei Wang

Senior Research Investigator

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wei.wang@pennmedicine.upenn.edu

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About

Wei Wang received his PhD degree in Statistics. His research interests include causal inference, mixed effects models, observational studies, cluster randomized trials, and applications to medical and health sciences.

Wei Wang

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About

Economic Modeling to Understand the Relationship Between Clinicians and Outcomes of Mechanically Ventilated Patients

Implementing Nudges to Promote Utilization of Low Tidal Volume Ventilation (INPUT) Study

Advancing the Design, Analysis, and Interpretation of Acute Respiratory Distress Syndrome Trials Using Modern Statistical Tools

Developing Methods to Analyze Data Missing Due to Death in Cluster Randomized Trials

Benefits of ICU Admission for Patients with Acute Respiratory Failure or Sepsis: A Mixed-Methods Study Across 26 Hospitals

Identifying patient subgroups and processes of care that cause outcome differences following ICU vs. ward triage among patients with acute respiratory failure and sepsis

Association of ICU admission and outcomes in sepsis and acute respiratory failure

Hospital strain and variation in sepsis ICU admission practices and associated outcomes

Among-hospital variation in intensive care unit admission practices and associated outcomes for patients with acute respiratory failure

A bayesian approach for estimating the survivor average causal effect when outcomes are truncated by death in cluster-randomized trials

Prediction of in-hospital mortality among intensive care unit patients using modified daily Laboratory-based Acute Physiology Score, version 2

A mixed model approach to estimate the survivor average causal effect in cluster-randomized trials

Wei Wang

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Current Projects

Economic Modeling to Understand the Relationship Between Clinicians and Outcomes of Mechanically Ventilated Patients

Implementing Nudges to Promote Utilization of Low Tidal Volume Ventilation (INPUT) Study

Advancing the Design, Analysis, and Interpretation of Acute Respiratory Distress Syndrome Trials Using Modern Statistical Tools

Developing Methods to Analyze Data Missing Due to Death in Cluster Randomized Trials

Benefits of ICU Admission for Patients with Acute Respiratory Failure or Sepsis: A Mixed-Methods Study Across 26 Hospitals

Identifying patient subgroups and processes of care that cause outcome differences following ICU vs. ward triage among patients with acute respiratory failure and sepsis

Related Publications

Association of ICU admission and outcomes in sepsis and acute respiratory failure

Hospital strain and variation in sepsis ICU admission practices and associated outcomes

Among-hospital variation in intensive care unit admission practices and associated outcomes for patients with acute respiratory failure

A bayesian approach for estimating the survivor average causal effect when outcomes are truncated by death in cluster-randomized trials

Prediction of in-hospital mortality among intensive care unit patients using modified daily Laboratory-based Acute Physiology Score, version 2

A mixed model approach to estimate the survivor average causal effect in cluster-randomized trials